@STRING{ACCV = {Proc. Asian Conf. Comp. Vis.}}

@STRING{CVIU = {Comp. Vis. Image Understanding}}

@STRING{CVPR = {Proc. IEEE Conf. Comp. Vis. Patt. Recogn.}}

@STRING{ECCV = {Proc. Eur. Conf. Comp. Vis.}}

@STRING{ICCV = {Proc. IEEE Conf. Comp. Vis.}}

@STRING{ICIP = {Proc. IEEE Conf. Image Process.}}

@STRING{ICML = {Proc. Int. Conf. Mach. Learn.}}

@STRING{ICLR = {Proc. Int. Conf. Learn. Represent.}}

@STRING{IEEE_J_CASVT = {{IEEE} Trans. Circuits Syst. Video Technol.}}

@STRING{TPAMI = {{IEEE} Trans. Pattern Anal. Mach. Intell.}}

@STRING{TNNLS = {{IEEE} Trans. Neural Network learn. Syst.}}

@STRING{TIP = {{IEEE} Trans. Image Proc.}}

@STRING{IEEE_J_TMM = {{IEEE} Trans. Multimedia}}

@STRING{IJCV = {Int. J. Comp. Vis.}}

@STRING{JMLR = {J. Mach. Learn. Res.}}

@STRING{ML = {Mach. Learn.}}

@STRING{MS = {Management Sci.}}

@STRING{NIPS = {Proc. Adv. Neural Inf. Process. Syst.}}

@STRING{PR = {Pattern Recogn.}}

@STRING{SIGIR = {Proc. ACM  Conf. Inf. Ret.}}

@STRING{VLDB = {Proc. Int. Conf. Very Large Databases}}

@STRING{AISTATS = {Proc. Int. Conf. Artif. Intell. Stat.}}

@STRING{TOIS = {{ACM} Trans. Inf. Syst.}}

@STRING{AAAI = {Proc. AAAI Conf. Artif. Intell.}}


@inproceedings{XNOR,
	Author = {Mohammad Rastegari and Vicente Ordonez and Joseph Redmon and Ali Farhadi},
	Title = {XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks},
	Booktitle = ECCV,
	Year = {2016}
}

@article{Caffe,
	Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
	Journal = {arXiv preprint arXiv:1408.5093},
	Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
	Year = {2014}
}

@inproceedings{TWN,
	Author = {Li, Fengfu and Zhang, Bo and Liu, Bin},
	booktitle = {The 1st International Workshop on Efficient Methods for Deep Neural Networks},
	Title = {Ternary Weight Networks},
	Year = {2016}
}

@inproceedings{BNN,
	title={Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1},
	author={Courbariaux, Matthieu and Hubara, Itay and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua},
	Booktitle = NIPS,
	pages = {4107--4115},
	year = {2016},
}

@inproceedings{MobileNet,
	title     = {MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications},
	author={Howard, Andrew G and Zhu, Menglong and Chen, Bo and Kalenichenko, Dmitry and Wang, Weijun and Weyand, Tobias and Andreetto, Marco and Adam, Hartwig},
	Booktitle = {forthcoming},
	year      = {2017},
}

@article{ShuffleNet,
	title={Shufflenet: An extremely efficient convolutional neural network for mobile devices},
	author={Zhang, Xiangyu and Zhou, Xinyu and Lin, Mengxiao and Sun, Jian},
	journal={arXiv preprint arXiv:1707.01083},
	year={2017}
}


@inproceedings{BC,
	title={Binaryconnect: Training deep neural networks with binary weights during propagations},
	author={Courbariaux, Matthieu and Bengio, Yoshua and David, Jean-Pierre},
	Booktitle=NIPS,
	pages={3123--3131},
	year={2015}
}

@inproceedings{AlexNet,
	title={Imagenet classification with deep convolutional neural networks},
	author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
	booktitle=NIPS,
	pages={1097--1105},
	year={2012}
}

@inproceedings{VGG,
	title={Very deep convolutional networks for large-scale image recognition},
	author={Simonyan, Karen and Zisserman, Andrew},
	booktitle=ICLR,
	year={2015}
}

@inproceedings{GoogLeNet,
	title={Going deeper with convolutions},
	author={Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent and Rabinovich, Andrew},
	booktitle=CVPR,
	pages={1--9},
	year={2015}
}

@inproceedings{ResNet,
	title={Deep residual learning for image recognition},
	author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
	Booktitle = CVPR,
	pages={770--778},
	year={2016}
}

@inproceedings{BatchNormal,
	title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
	author={Ioffe, Sergey and Szegedy, Christian},
	booktitle=ICML,
	pages={448--456},
	year={2015}
}

@inproceedings{HORQ,
	title={Performance Guaranteed Network Acceleration via High-Order Residual Quantization},
	author={Li, Zefan and Ni, Bingbing and Zhang, Wenjun and Yang, Xiaokang and Gao, Wen},
	booktitle=ICCV,
	year={2017}
}

@article{SqueezeNet,
	title={SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $<$ 0.5 MB model size},
	author={Iandola, Forrest N and Han, Song and Moskewicz, Matthew W and Ashraf, Khalid and Dally, William J and Keutzer, Kurt},
	journal={arXiv preprint arXiv:1602.07360},
	year={2016}
}

@inproceedings{LocalBCNN,
	title={Local Binary Convolutional Neural Networks},
	author={Juefei-Xu, Felix and Boddeti, Vishnu Naresh and Savvides, Marios},
	booktitle=CVPR,
	year={2017}
}

@inproceedings{LCNN,
	title={LCNN: Lookup-based Convolutional Neural Network},
	author={Bagherinezhad, Hessam and Rastegari, Mohammad and Farhadi, Ali},
	booktitle=CVPR,
	year={2017}
}

@inproceedings{EBP,
	title={Expectation backpropagation: Parameter-free training of multilayer neural networks with continuous or discrete weights},
	author={Soudry, Daniel and Hubara, Itay and Meir, Ron},
	booktitle=NIPS,
	pages={963--971},
	year={2014}
}

@inproceedings{DoReFa,
	title={DoReFa-Net: Training low bitwidth convolutional neural networks with low bitwidth gradients},
	author={Zhou, Shuchang and Wu, Yuxin and Ni, Zekun and Zhou, Xinyu and Wen, He and Zou, Yuheng},
	booktitle=CVPR,
	year={2016}
}

@inproceedings{TTQ,
	title={Trained ternary quantization},
	author={Zhu, Chenzhuo and Han, Song and Mao, Huizi and Dally, William J},
	booktitle=ICLR,
	year={2017}
}

@article{GXNOR,
	title={Gated XNOR Networks: Deep Neural Networks with Ternary Weights and Activations under a Unified Discretization Framework},
	author={Deng, Lei and Jiao, Peng and Pei, Jing and Wu, Zhenzhi and Li, Guoqi},
	journal={arXiv preprint arXiv:1705.09283},
	year={2017}
}

@article{QNN,
	title={Quantized neural networks: Training neural networks with low precision weights and activations},
	author={Hubara, Itay and Courbariaux, Matthieu and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua},
	journal={arXiv preprint arXiv:1609.07061},
	year={2016}
}

@inproceedings{Q-CNN,
	title={Quantized convolutional neural networks for mobile devices},
	author={Wu, Jiaxiang and Leng, Cong and Wang, Yuhang and Hu, Qinghao and Cheng, Jian},
	booktitle=CVPR,
	pages={4820--4828},
	year={2016}
}

@inproceedings{FFN,
	title={Fixed-point Factorized Networks},
	author={Wang, Peisong and Cheng, Jian},
	booktitle=CVPR,
	year={2017}
}

@inproceedings{TNN,
	title={Ternary neural networks for resource-efficient AI applications},
	author={Alemdar, Hande and Leroy, Vincent and Prost-Boucle, Adrien and P{\'e}trot, Fr{\'e}d{\'e}ric},
	booktitle={Neural Networks (IJCNN), 2017 International Joint Conference on},
	pages={2547--2554},
	year={2017},
	organization={IEEE}
}

@inproceedings{Adam,
	title={Adam: A method for stochastic optimization},
	author={Kingma, Diederik and Ba, Jimmy},
	booktitle=ICLR,
	year={2015}
}

@inproceedings{dai2016r,
	title={R-fcn: Object detection via region-based fully convolutional networks},
	author={Dai, Jifeng and Li, Yi and He, Kaiming and Sun, Jian},
	booktitle=NIPS,
	pages={379--387},
	year={2016}
}

@article{lecun2015deep,
	title={Deep learning},
	author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
	journal={Nature},
	volume={521},
	number={7553},
	pages={436--444},
	year={2015},
	publisher={Nature Research}
}

@inproceedings{redmon2016yolo9000,
	title={YOLO9000: better, faster, stronger},
	author={Redmon, Joseph and Farhadi, Ali},
	booktitle=CVPR,
	pages={7263--7271},
	year={2017}
}

@inproceedings{liu2016ssd,
	title={Ssd: Single shot multibox detector},
	author={Liu, Wei and Anguelov, Dragomir and Erhan, Dumitru and Szegedy, Christian and Reed, Scott and Fu, Cheng-Yang and Berg, Alexander C},
	booktitle=ECCV, 
	pages={21--37},
	year={2016},
}

@inproceedings{ren2015faster,
	title={Faster R-CNN: Towards real-time object detection with region proposal networks},
	author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
	booktitle=NIPS,
	pages={91--99},
	year={2015}
}

@inproceedings{girshick2014rich,
	title={Rich feature hierarchies for accurate object detection and semantic segmentation},
	author={Girshick, Ross and Donahue, Jeff and Darrell, Trevor and Malik, Jitendra},
	booktitle=CVPR,
	pages={580--587},
	year={2014}
}

@inproceedings{girshick2015fast,
	title={Fast R-cnn},
	author={Girshick, Ross},
	booktitle= ICCV,
	pages={1440--1448},
	year={2015}
}

@inproceedings{long2015fully,
	title={Fully convolutional networks for semantic segmentation},
	author={Long, Jonathan and Shelhamer, Evan and Darrell, Trevor},
	booktitle=CVPR,
	pages={3431--3440},
	year={2015}
}

@inproceedings{pinheiro2015learning,
	title={Learning to segment object candidates},
	author={Pinheiro, Pedro O and Collobert, Ronan and Doll{\'a}r, Piotr},
	booktitle=NIPS,
	pages={1990--1998},
	year={2015}
}

@inproceedings{han2015deep,
	title={Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding},
	author={Han, Song and Mao, Huizi and Dally, William J},
	booktitle=ICLR,
	year={2016}
}

@inproceedings{han2015learning,
	title={Learning both weights and connections for efficient neural network},
	author={Han, Song and Pool, Jeff and Tran, John and Dally, William},
	booktitle=NIPS,
	pages={1135--1143},
	year={2015}
}

@inproceedings{wen2016learning,
	title={Learning structured sparsity in deep neural networks},
	author={Wen, Wei and Wu, Chunpeng and Wang, Yandan and Chen, Yiran and Li, Hai},
	booktitle=NIPS,
	pages={2074--2082},
	year={2016}
}

@inproceedings{soudry2014expectation,
	title={Expectation backpropagation: Parameter-free training of multilayer neural networks with continuous or discrete weights},
	author={Soudry, Daniel and Hubara, Itay and Meir, Ron},
	booktitle=NIPS,
	pages={963--971},
	year={2014}
}

@inproceedings{wu2016quantized,
	title={Quantized convolutional neural networks for mobile devices},
	author={Wu, Jiaxiang and Leng, Cong and Wang, Yuhang and Hu, Qinghao and Cheng, Jian},
	booktitle=CVPR,
	pages={4820--4828},
	year={2016}
}

@inproceedings{zhou2017incremental,
	title={Incremental network quantization: Towards lossless cnns with low-precision weights},
	author={Zhou, Aojun and Yao, Anbang and Guo, Yiwen and Xu, Lin and Chen, Yurong},
	booktitle=ICLR,
	year={2017}
}

@inproceedings{lebedev2014speeding,
	title={Speeding-up convolutional neural networks using fine-tuned cp-decomposition},
	author={Lebedev, Vadim and Ganin, Yaroslav and Rakhuba, Maksim and Oseledets, Ivan and Lempitsky, Victor},
	booktitle=ICLR,
	year={2015}
}

@inproceedings{jaderberg2014speeding,
	title={Speeding up convolutional neural networks with low rank expansions},
	author={Jaderberg, Max and Vedaldi, Andrea and Zisserman, Andrew},
	booktitle={BMVC},
	year={2014}
}

@article{jin2014flattened,
	title={Flattened convolutional neural networks for feedforward acceleration},
	author={Jin, Jonghoon and Dundar, Aysegul and Culurciello, Eugenio},
	journal={arXiv preprint arXiv:1412.5474},
	year={2014}
}

@inproceedings{hinton2015distilling,
	title={Distilling the knowledge in a neural network},
	author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
	booktitle={NIPS 2014 Deep Learning and Representation Learning Workshop},
	year={2014}
}

@inproceedings{he2015delving,
	title={Delving deep into rectifiers: Surpassing human-level performance on imagenet classification},
	author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
	booktitle=ICCV,
	pages={1026--1034},
	year={2015}
}

@inproceedings{huang2016densely,
	title={Densely connected convolutional networks},
	author={Huang, Gao and Liu, Zhuang and Weinberger, Kilian Q and van der Maaten, Laurens},
	booktitle=CVPR,
	year={2017}
}

@inproceedings{he2016identity,
	title={Identity mappings in deep residual networks},
	author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
	booktitle=ECCV,
	pages={630--645},
	year={2016},
}

@article{chen2017,
	title={Dual Path Networks},
	author={Yunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng},
	journal={arXiv preprint arXiv:1707.01629},
	year={2017}
}

@inproceedings{xie2016aggregated,
	title={Aggregated residual transformations for deep neural networks},
	author={Xie, Saining and Girshick, Ross and Doll{\'a}r, Piotr and Tu, Zhuowen and He, Kaiming},
	booktitle=CVPR,
	year={2017}
}

@article{MNIST,
	title={Gradient-based learning applied to document recognition},
	author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
	journal={Proceedings of the IEEE},
	volume={86},
	number={11},
	pages={2278--2324},
	year={1998},
	publisher={IEEE}
}

@article{ImageNet,
	title={Imagenet large scale visual recognition challenge},
	author={Russakovsky, Olga and Deng, Jia and Su, Hao and Krause, Jonathan and Satheesh, Sanjeev and Ma, Sean and Huang, Zhiheng and Karpathy, Andrej and Khosla, Aditya and Bernstein, Michael and others},
	journal=IJCV,
	volume={115},
	number={3},
	pages={211--252},
	year={2015},
	publisher={Springer}
}

@article{CIFAR10,
	title={Learning multiple layers of features from tiny images},
	author={Krizhevsky, Alex and Hinton, Geoffrey},
	year={2009},
	publisher={Technical report, University of Toronto}
}

@inproceedings{SVHN,
  title={Reading digits in natural images with unsupervised feature learning},
  author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},
  booktitle={NIPS workshop on deep learning and unsupervised feature learning},
  volume={2011},
  number={2},
  pages={5},
  year={2011}
}

@misc{pascal-voc-2012,
	author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
	title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults",
	howpublished = "http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html"
}

@misc{pascal-voc-2007,
	author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
	title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2007 {(VOC2007)} {R}esults",
	howpublished = "http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html"}

@inproceedings{BinaryNet,
	title={How to train a compact binary neural network with high accuracy?},
	author={Tang, Wei and Hua, Gang and Wang, Liang},
	booktitle=AAAI,
	pages={2625--2631},
	year={2017}
}

@article{Kim2015BitwiseNN,
	title={Bitwise Neural Networks},
	author={Minje Kim and Paris Smaragdis},
	journal={CoRR},
	year={2015},
	volume={abs/1601.06071}
}

@inproceedings{denton2014exploiting,
  title={Exploiting linear structure within convolutional networks for efficient evaluation},
  author={Denton, Emily L and Zaremba, Wojciech and Bruna, Joan and LeCun, Yann and Fergus, Rob},
  booktitle=NIPS,
  pages={1269--1277},
  year={2014}
}

@inproceedings{denil2013predicting,
  title={Predicting parameters in deep learning},
  author={Denil, Misha and Shakibi, Babak and Dinh, Laurent and De Freitas, Nando and others},
  booktitle=NIPS,
  pages={2148--2156},
  year={2013}
}
@article{kim2015compression,
  title={Compression of deep convolutional neural networks for fast and low power mobile applications},
  author={Kim, Yong-Deok and Park, Eunhyeok and Yoo, Sungjoo and Choi, Taelim and Yang, Lu and Shin, Dongjun},
  journal={arXiv preprint arXiv:1511.06530},
  year={2015}
}

@inproceedings{wang2016accelerating,
  title={Accelerating convolutional neural networks for mobile applications},
  author={Wang, Peisong and Cheng, Jian},
  booktitle={Proceedings of the 2016 ACM on Multimedia Conference},
  pages={541--545},
  year={2016},
  organization={ACM}
}
@article{zhang2016accelerating,
  title={Accelerating very deep convolutional networks for classification and detection},
  author={Zhang, Xiangyu and Zou, Jianhua and He, Kaiming and Sun, Jian},
  journal=TPAMI,
  volume={38},
  number={10},
  pages={1943--1955},
  year={2016},
  publisher={IEEE}
}
@article{courbariaux2014low,
  title={Low precision arithmetic for deep learning},
  author={Courbariaux, Matthieu and Bengio, Yoshua and David, J},
  journal={CoRR, abs/1412.7024},
  volume={4},
  year={2014}
}

@inproceedings{gupta2015deep,
  title={Deep learning with limited numerical precision},
  author={Gupta, Suyog and Agrawal, Ankur and Gopalakrishnan, Kailash and Narayanan, Pritish},
  booktitle=ICML,
  pages={1737--1746},
  year={2015}
}

@inproceedings{lin2016fixed,
  title={Fixed point quantization of deep convolutional networks},
  author={Lin, Darryl and Talathi, Sachin and Annapureddy, Sreekanth},
  booktitle=ICML,
  pages={2849--2858},
  year={2016}
}

@inproceedings{lin2015neural,
  title={Neural networks with few multiplications},
  author={Lin, Zhouhan and Courbariaux, Matthieu and Memisevic, Roland and Bengio, Yoshua},
  booktitle=ICLR,
  year={2016}
}

@inproceedings{ambai2016ternary,
  title={Ternary Weight Decomposition and Binary Activation Encoding for Fast and Compact Neural Network},
  author={Ambai, Mitsuru and Matsumoto, Takuya and Yamashita, Takayoshi and Fujiyoshi, Hironobu},
  booktitle=ICLR,
  year={2017}
}
@inproceedings{ambai2014spade,
  title={SPADE: scalar product accelerator by integer decomposition for object detection},
  author={Ambai, Mitsuru and Sato, Ikuro},
  booktitle=ECCV,
  pages={267--281},
  year={2014},
}